SOTAVerified

Reinforcement Learning (RL)

Reinforcement Learning (RL) involves training an agent to take actions in an environment to maximize a cumulative reward signal. The agent interacts with the environment and learns by receiving feedback in the form of rewards or punishments for its actions. The goal of reinforcement learning is to find the optimal policy or decision-making strategy that maximizes the long-term reward.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2651–2700 of 15113 papers

TitleStatusHype
A Generalised and Adaptable Reinforcement Learning Stopping MethodCode0
Stabilizing Temporal Difference Learning via Implicit Stochastic Recursion—0
A General Approach of Automated Environment Design for Learning the Optimal Power Flow—0
SmallPlan: Leverage Small Language Models for Sequential Path Planning with Simulation-Powered, LLM-Guided DistillationCode0
MULE: Multi-terrain and Unknown Load Adaptation for Effective Quadrupedal Locomotion—0
Leveraging Partial SMILES Validation Scheme for Enhanced Drug Design in Reinforcement Learning Frameworks—0
Directly Forecasting Belief for Reinforcement Learning with DelaysCode0
Implicit Neural-Representation Learning for Elastic Deformable-Object Manipulations—0
Adaptive 3D UI Placement in Mixed Reality Using Deep Reinforcement Learning—0
Phi-4-reasoning Technical Report—0
Reinforced MLLM: A Survey on RL-Based Reasoning in Multimodal Large Language Models—0
Phi-4-Mini-Reasoning: Exploring the Limits of Small Reasoning Language Models in Math—0
Enhancing New-item Fairness in Dynamic Recommender SystemsCode0
PRISM: Projection-based Reward Integration for Scene-Aware Real-to-Sim-to-Real Transfer with Few Demonstrations—0
A Survey on GUI Agents with Foundation Models Enhanced by Reinforcement Learning—0
Token-Efficient RL for LLM Reasoning—0
AI Recommendation Systems for Lane-Changing Using Adherence-Aware Reinforcement Learning—0
Reinforcement Learning-Based Heterogeneous Multi-Task Optimization in Semantic Broadcast Communications—0
Interactive Double Deep Q-network: Integrating Human Interventions and Evaluative Predictions in Reinforcement Learning of Autonomous Driving—0
An Automated Reinforcement Learning Reward Design Framework with Large Language Model for Cooperative Platoon Coordination—0
LLMs for Engineering: Teaching Models to Design High Powered Rockets—0
BQSched: A Non-intrusive Scheduler for Batch Concurrent Queries via Reinforcement LearningCode0
Depth-Constrained ASV Navigation with Deep RL and Limited Sensing—0
Explainable AI for UAV Mobility Management: A Deep Q-Network Approach for Handover Minimization—0
LLM-hRIC: LLM-empowered Hierarchical RAN Intelligent Control for O-RAN—0
SAPO-RL: Sequential Actuator Placement Optimization for Fuselage Assembly via Reinforcement Learning—0
Integrating Learning-Based Manipulation and Physics-Based Locomotion for Whole-Body Badminton Robot Control—0
Training Large Language Models to Reason via EM Policy Gradient—0
Reinforcement learning framework for the mechanical design of microelectronic components under multiphysics constraints—0
Data-Assimilated Model-Based Reinforcement Learning for Partially Observed Chaotic Flows—0
Offline Robotic World Model: Learning Robotic Policies without a Physics Simulator—0
Natural Policy Gradient for Average Reward Non-Stationary RL—0
Monte Carlo Planning with Large Language Model for Text-Based Game Agents—0
Hybrid Reinforcement Learning and Model Predictive Control for Adaptive Control of Hydrogen-Diesel Dual-Fuel Combustion—0
Insights from Verification: Training a Verilog Generation LLM with Reinforcement Learning with Testbench Feedback—0
Real-Time Optimal Design of Experiment for Parameter Identification of Li-Ion Cell Electrochemical Model—0
StreamRL: Scalable, Heterogeneous, and Elastic RL for LLMs with Disaggregated Stream Generation—0
SARI: Structured Audio Reasoning via Curriculum-Guided Reinforcement Learning—0
SLiM-Gym: Reinforcement Learning for Population Genetics—0
Policy-Based Radiative Transfer: Solving the 2-Level Atom Non-LTE Problem using Soft Actor-Critic Reinforcement Learning—0
LAPP: Large Language Model Feedback for Preference-Driven Reinforcement Learning—0
Dynamic Contrastive Skill Learning with State-Transition Based Skill Clustering and Dynamic Length Adjustment—0
Think2SQL: Reinforce LLM Reasoning Capabilities for Text2SQL—0
OTC: Optimal Tool Calls via Reinforcement Learning—0
Relation-R1: Cognitive Chain-of-Thought Guided Reinforcement Learning for Unified Relational Comprehension—0
Mixed-Precision Conjugate Gradient Solvers with RL-Driven Precision Tuning—0
Quantum-Enhanced Reinforcement Learning for Power Grid Security Assessment—0
Unlearning Works Better Than You Think: Local Reinforcement-Based Selection of Auxiliary Objectives—0
Improving RL Exploration for LLM Reasoning through Retrospective Replay—0
SwitchMT: An Adaptive Context Switching Methodology for Scalable Multi-Task Learning in Intelligent Autonomous Agents—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PPGMean Normalized Performance0.76—Unverified
2PPOMean Normalized Performance0.58—Unverified